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Proteomic Approaches and Reviews on Cancer Biomarker Researches - Literature review Example

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This work "Proteomic Approaches and Reviews on Cancer Biomarker Researches" describes the war against cancer. The author outlines round technology, software, and physics, biotechnology, and chemistry in a bid to lower the mortality rate. From this work, it is clear about better treatment and prevention…
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Proteomic Approaches and Reviews on Cancer Biomarker Researches
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Have proteomic approaches advanced reviews on cancer biomarker researches College The war against cancer has becomemore vile in the world, nearly half million people in the United States alone die each year from cancer while research shows that more and more people at least acquire cancer in their lifetime. Resources are therefore being put together at speed in all round technology, software and physics, biotechnology and chemistry in bid to lower the mortality rate. Platforms have been laid to study the cause of these ailments at a molecular level. Both proteomics and genomics have advanced the study of the disease process in providing knowledge on a molecular complexity. They are advancing to ensure there is especially detection of the biomarkers early to create better treatment and prevention ( Miler et al 2001.) Introduction and biomarkers. Biomarkers are among the devised way of fighting cancer by detecting it early and in prevention of cancer along with enhancing their treatment. A cancer biomarker refers to a biological molecule found in the body tissues, fluids and the blood that are an indication of a normal or abnormal process of cancer. Cancer biomarkers are useful in realizing the presence of the condition as well as fighting against it. Some of the known various forms of cancer biomarkers include protein subgroups like enzymes, receptors and glycoproteins along with hormones. Other types of cancer biomarkers include changes in genetic mutations, changes in generic signatures and amplifications, these changes are aspects in determining the process of cancer. Cancer biomarkers are also known as tumor markers. Cancer biomarkers are grouped according to their functional purpose as screening (diagnostic) biomarkers, prognostic biomarkers and stratification biomarkers among others. For biomarkers to be useful, they must be linked with tested and approved improvements in the quality of life and aid surviving the ailments as well as good patient outcome (Kristoff 2011.) Proteomics. Proteomic knowledge refers to knowledge that pertains to the protein content of the cell proteomics allow for splitting of the various mRNAs and expressing how the genes and soft genes of regulation are in contrast with genomes, it is more dynamic than the genome and consists of other forms of gene expression involving. Proteomic technologies are adoptive in quite accurate expressions resulted to by a disease activity. The advantage of proteomic technology is borne in the fact that the protein itself is the highest point of expression of these protein activities. Development of biomarkers based on genomic technologies involve measuring full sets of expression of mRNA like differential display, gene expression arrays along with serial analysis of expression of genes. Developing challenges has been challenged by a non-complete utilization of resource for example proteolysis cleavage and modifications like phosphorylation. The most widely used method of separating proteins is two dimensional which is a gel utilizing method of electrophoresis. In this method, proteins are first separated with their isoelectric points then separated with their molecular masses. Using mobilized pH values and gradients for the first step, increases the power to resolve. It is useful in detecting proteins of low abundance. The method of two dimensional gel is useful in analyzing a whole cell or tissue extracts of proteins. Two dimensional method is useful in separation of complex mixtures of proteins, reached at by obtaining the ratios of independent spot intensities on two dimensional gels. Mass based techniques are efficient because most compounds are identical to their natural counterparts in isotope and chemical properties and only vary in their masses (Tansky 2009.) The MALDI MS. (Gel based methods). This method in biochemistry of cancer requires more sensitive tools. Its initial purpose beckons to achieve partial sequences of proteins to identify and obtain the design for oligonucleotide useful in cloning genes. The methods is a low sensitive kind and requires a lot of material to detect certain protein that exist in an abundance scarcity. The MALDI utilizes an ionization technique that utilizes a mass spectrometer, the mass spectrometer measure molecular masses. MALDI creates a useful gaseous form of the protein selected molecules with a sufficient matrix material such as dihydroxybenzoic acid into a solid material. Using laser pulses, the precipitate is the irradiated causing the matrix material to impart energy on the biomolecules. The matrix material absorption of the laser wavelengths subjects the molecules to desorption and ionization that essentially leads to fragmentation. The mass spectrometer then measures the ratio of mass to charge (m/z) of the protein, peptide fragments or the peptide itself. The analysis of proteins is carried out after gel separated proteins have undergone enzymatic degradation. The power of MS has created such systems that are integrated into robotic machinery to pick out two specified points on a two dimensional gel. LC/MS (non-gel based methods). LC involves concentrating and then separating peptides from very complex mixtures of peptides and then later sequencing them with MS. The ability of the tandem mass spectrometer to sequence information for specific peptides in a sample of mixed peptides. The LC-MS/MS method has been revealed in its abilities to enhance separation of analytes in the femtomolar range and in their identification. Along with the tandem spectrum, the LC-MS method incorporates HPLC pumps. These two elements are linked to the same software to enhance good coordination in obtaining both the chromatography and ionic detection. The samples are incorporated into the system by an injector or pressure cell to boost sensitivity as well as using pre column traps along with vented micro capillary columns. After passing through the HPLC columns, peptides are put through ionization by electrospray before being analyzed by the tandem mass spectrometer. The ions are then passed from the ejector to the ion trap according to the ratios of mass to charge (m/z) (Conn 2003.) From the ion trap, a particular peptide can then be followed by an ejection of ions with certain charges relating to it from the ion trap. One LC-MS analysis raises possibilities of identifying in isolation and sequencing over hundreds of selected peptides from a single sample. This method is open to creating pathways to greater discoveries in biomarkers that could be useful in research to aid the understanding of mechanisms via which environmental exposure may cause carcinogenesis by mutation of proteins. The LC-MS is a highly developed approach with great advantages it has been used in managing congenital adrenal hyperplasia from full paper blood samples. The approach is also useful in its ability to targets of and link adducts to certain select amino acids. Quantitative methods/ label free quantitative MS. All label free proteomic methods include; preparation of the protein samples which involves extracting the proteins, reduction, alkylation and digestion respectively. The sample is separated by liquid chromatography LC and analyzed by MS. The other step involves analyzing the data and involves identifying the peptide, quantifying the peptides and their statistical analysis. Unlike in the labelling process where the samples are created from a combination of mixtures that are later taken through the analyzing process. The label free process involves preparation of samples separately that are later individually subjected to the LC-MS process. Two categories of measurements are engaged in the quantification process that involve changes in the intensities of ions, peptide peak areas and varying peptide heights during chromatography. The peptide peak intensities are measured by directly comparing their analyses. Protein peptides reflect changes in the levels of protein and protein abundance. Label free techniques use some of the detection methods as surface Plasmon resonance, carbon nanotubes and mass spectrometry SELDI-TOF. NON MASS SPEC BASED METHODS. Microarray based methods. Micro array based methods are a set of some of the advanced proteomic methods on cancer biomarkers. Its advantages lay in the efficiency to study more numbers of protein types simultaneously. Micro array approach has come emergent with a number of protein microarrays such as microarrays for lectin and tissue, capture micro arrays and cell free expression micro arrays. The micro array approach has developed vaccine creating processes and profiling of immunology as well as protein substrate interactions to obtain the possible resolutions proteomic technologies can develop. Emerging micro array developments are coupled with sensitive systems of detection to function effectively. Most microarray based methods are also label free kind of systems for the sake of functional efficiency. The forward phase format involves molecules immobilized on slides the molecules are usually antibodies, they are then incubated with the specimens selected and are screened for biomarkers tis happens in a single test. The reverse phase on the other hand fluids as urine and serum and tissue, the analytes are screened against a single marker at a time (Matson R 2007.) What are the challenges for proteomics in the field of cancer biomarker research? Even with high proteomic technologies to research on cancer biomarkers and create preventive measures along with treatment procedures for cancerous conditions challenges are present in structural forms of tissues and proteins as well as new developments (Nass et al 2007.) Tissue samples for example are a disadvantage when being used to conduct experiments compared to cell lines, they have a limited life unlike the cell lines and their structures differ in organisation the organisation of cell lines is more reliable since it is also very consistent. The tissues cells on the other hand have slow proliferation which makes the process of creating specimens a little more complicated. Even with the increased importance and urgency for proteomics in biomedical science other challenges for advancement of these studies as lack of availability of tissue or access has been rampant. These tissues and experimental studies are useful in strengthening hypothesis knowledge to dependency levels so as to avoid unseen predicaments during actual treatment (Anderson 2004.) There is also need for non-invasive markers in the assessment of progressive ailments such as fibrosis. For example liver biopsis have been used as the ‘SI unit’ standards for determining liver fibrosis, presence and progression (Hoffmann 2007…Strobaat 2006.) To study the mrna and other profiles of protein disease in liver biopsies is challenging, the challenges arise in the small size of the tissue samples as well as the biopsies being that which contain many different cell types. Studying a cell population will also require micro dissection with the help of laser capture. Invasive procedures are used where the samples to be used especially fluids are hard , near impossible to obtain. Sensitivity of proteomic methods. Very highly sensitive approaches both mass and non mass along with gel and non gel methods are useful in the development of good proteomic advancements. The greater the sensitivity of the methods the more accurate results the biomarkers are expected to give. The sensitivity of the process is therefore a matter of high training and experience it is important that the hypothesis made be tested to avoid malfunctions. Some of the processes however due to lengthy processes of cell development and scarcities will take years to develop and be established (Ivanov 2011.) Complexities of blood. Blood is the most sampled fluid and reason can only have it rightful to assume that using the right technology, it is possible to detect most tissue protein (Anderson et al 2004), its proteome however presents the most complicated of all the body proteomes (Anderson and Anderson 2004) complexities in blood will therefore lead to challenges in proteomic processes. Its dynamic range leads to complications with 12 orders of magnitude along with the constitution of proteins where biomarkers essentially constitute of 1% of the proteins whilst plasma constitutes of the rest 99% (Tirumalai et al.) Biomarker discovery pipeline. A software development for determining and analysing sets of data performance. The software is set to facilitate high performance in response and accuracy, the software is accustomed for m/z functioning with points to identify biomarkers. Recent developments show that technologies as these are capable of computing all humans’ protein set by the Human Proteome organisation (Campbell et al 2003.) Proteomic approaches have played a significant role in detecting malignancies early and aiding in selecting therapeutic protocol to deal with threats of cancer. It is advancing with technology and adopting to changes in structural and functional molecular formations (Sanchez et al 2004.) Bibliography ALBERTS, D. S. (2004). Cancer biomarkers. Amsterdam, IOS Press. AZUAJE, F. (2010). Bioinformatics and biomarker discovery: "omic" data analysis for personalised medicine. Hoboken, NJ, John Wiley & Sons. BURCZYNSKI, M. E., & ROCKETT, J. C. (2006). Surrogate tissue analysis: genomic, proteomic and metabolomic approaches. Boca Raton, CRC Press. CAMPBELL, A. M., & HEYER, L. J. (2003). Discovering genomics, proteomics, and bioinformatics. San Francisco, Benjamin Cummings. CONN, P. M. (2003). Handbook of proteomic methods. Totowa, NJ, Humana Press. Dembowy, Joanna. Functional Proteomic Approaches for the Analysis of a Dynamic Signaling Pathway. , (2003). Genomic & proteomic technological advances in cancer research. 2005. Print. MOODY, G. (2004). Digital code of life: how bioinformatics is revolutionizing science, medicine, and business. Hoboken, N.J., Wiley. NASS, S. J., & MOSES, H. L. (2007). Cancer biomarkers the promises and challenges of improving detection and treatment. Washington, D.C., National Academies Press. http://site.ebrary.com/id/10170927. Heymann, Dominique. Bone Cancer: Progression and Therapeutic Approaches. Amsterdam: Academic, 2010. Internet resource. HOFFMANN, E. D., & STROOBANT, V. (2007). Mass spectrometry: principles and applications. Chichester, West Sussex, England, J. Wiley. IVANOV, A. R., & LAZAREV, A. V. (2011). Sample preparation in biological mass spectrometry. Dordrecht [etc.], Springer. JORDAN, B. (2012). Microarrays in diagnostics and biomarker development current and future applications. Heidelberg, Springer. http://dx.doi.org/10.1007/978-3-642-28203-4. KRISTOFF, H. C. (2011). Cancer biomarkers. New York, Nova Science Publishers. MATSON, R. S. (2005). Applying genomic and proteomic microarray technology in drug discovery. Boca Raton, CRC Press. OPPENHEIMER SR, MI D, SANDERS ME, & CAPRIOLI RM. (2010). Molecular analysis of tumor margins by MALDI mass spectrometry in renal carcinoma. Journal of Proteome Research. 9, 2182-90. MILLER, A. B. (2001). Biomarkers in cancer chemoprevention. Lyon, International Agency for Research on Cancer. MÜLHARDT, C. (2007). Molecular biology and genomics. Amsterdam, Elsevier Academic Press. http://www.engineeringvillage.com/controller/servlet/OpenURL?genre=book&isbn=9780120885466. PETRICOIN, C. (2009). Proteomics in laboratory medicine. Philadelphia, PA, Saunders. RANCOURT, G. C. (2011). Proteomics: methods, applications and limitations. Hauppauge, N.Y., Nova Science Publishers. REINDERS, J., & SICKMANN, A. (2009). Proteomics. Dordrecht, Humana Press. SANCHEZ, J.-C., CORTHALS, G. L., & HOCHSTRASSER, D. F. (2004). Biomedical applications of proteomics. Weinheim, Wiley-VCH. SCHWAB, M. (2008). Encyclopedia of cancer. New York, Springer. http://0-find.galegroup.com.lib.rivier.edu/gvrl/infomark.do?type=aboutBook&prodId=GVRL&eisbn=9783540476481&version=1.0&userGroupName=nash91631&source=gale. TAINSKY, M. A. (2009). Tumor biomarker discovery: methods and protocols. New York, Humana. TAINSKY, M. A. (2010). Cancer Antibodies Cancer Biomarkers. Ios Pr Inc. YONA, G. (2011). Introduction to computational proteomics. Boca Raton, CRC Press. Read More
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